Technical Field
The present invention relates to detecting anomalous sensors.
Related Art
Detection of anomalous sensors is important in a variety of technical fields. It is often costly or almost impossible to monitor a great number of sensors with human eyes. Existing anomaly localization methods, such as the method disclosed in “T. Id'e, S. Papadimitriou, and M. Vlachos; COMPUTING CORRELATION ANOMALY SCORES USING STOCHASTIC NEAREST NEIGHBORS; Proceedings of the 7th IEEE International Conference on Data Mining, pages 523-528, 2007” determine a degree of anomaly of sensors. However, existing methods are computationally expensive, requiring lots of time, resources, or both, and do not indicate a degree of anomaly in an absolute sense, nor consider temporal information of sensor data.